{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#color = sns.color_palette()\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# path to where the data lies\n",
    "#dpath = './data/'\n",
    "data = pd.read_csv(\"day.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 去除无关特征\n",
    "data = data.drop(['instant','casual','registered'], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 显示数据基本信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 13 columns):\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(8), object(1)\n",
      "memory usage: 74.3+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dteday        0\n",
       "season        0\n",
       "yr            0\n",
       "mnth          0\n",
       "holiday       0\n",
       "weekday       0\n",
       "workingday    0\n",
       "weathersit    0\n",
       "temp          0\n",
       "atemp         0\n",
       "hum           0\n",
       "windspeed     0\n",
       "cnt           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 查看是否有空值\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           season          yr        mnth     holiday     weekday  workingday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     2.496580    0.500684    6.519836    0.028728    2.997264    0.683995   \n",
       "std      1.110807    0.500342    3.451913    0.167155    2.004787    0.465233   \n",
       "min      1.000000    0.000000    1.000000    0.000000    0.000000    0.000000   \n",
       "25%      2.000000    0.000000    4.000000    0.000000    1.000000    0.000000   \n",
       "50%      3.000000    1.000000    7.000000    0.000000    3.000000    1.000000   \n",
       "75%      3.000000    1.000000   10.000000    0.000000    5.000000    1.000000   \n",
       "max      4.000000    1.000000   12.000000    1.000000    6.000000    1.000000   \n",
       "\n",
       "       weathersit        temp       atemp         hum   windspeed          cnt  \n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000   731.000000  \n",
       "mean     1.395349    0.495385    0.474354    0.627894    0.190486  4504.348837  \n",
       "std      0.544894    0.183051    0.162961    0.142429    0.077498  1937.211452  \n",
       "min      1.000000    0.059130    0.079070    0.000000    0.022392    22.000000  \n",
       "25%      1.000000    0.337083    0.337842    0.520000    0.134950  3152.000000  \n",
       "50%      1.000000    0.498333    0.486733    0.626667    0.180975  4548.000000  \n",
       "75%      2.000000    0.655417    0.608602    0.730209    0.233214  5956.000000  \n",
       "max      3.000000    0.861667    0.840896    0.972500    0.507463  8714.000000  "
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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N1WlreUs+AYY658YD/wu81lQlM7vVzJab2fLSUv21JeHZXVHNht2VnDE8jfjYaL/DaRdn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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e3da6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 目标y（每天总租车人数）的直方图／分布\n",
    "fig = plt.figure()\n",
    "sns.distplot(data.cnt.values, bins=50, kde=True)\n",
    "plt.xlabel('Median value of cnt', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Su02MwBkkajbNuOq9AlC6vZm0IczDW+ouKQ2QzSoNmHV0hv+hPUPa50FlUB+/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\nIgAEQRDaFBEAgiAIbcr/Bw1EbIWHHgM8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f1749b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 单个特征cnt散点图\n",
    "plt.scatter(range(data.shape[0]), data[\"cnt\"].values,color='purple')\n",
    "plt.title(\"Distribution of cnt\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 输入特征的直方图/分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e4a78d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.season, order=[1,2,3,4]);\n",
    "plt.xlabel('season');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iJEmj12U112eahwTdwGBo6I6qmnGISZK0e5sxIJL8EvDfgB8wuBz1sCTvrqov912cJGl0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\nqQdoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fd6f9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.yr, order=[0,1]);\n",
    "plt.xlabel('yr');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e9637f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.mnth, order=[1,2,3,4,5,6,7,8,9,10,11,12]);\n",
    "plt.xlabel('mnth');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cJGl8+tzF9D7gl6pqE0CSZwOfAQwISdqL9RmD2D4dDs0dDOZWkiTtxZ7wDCLJyW311iRX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e432a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.holiday, order=[0,1]);\n",
    "plt.xlabel('holiday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f658b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.weekday, order=[0,1,2,3,4,5,6]);\n",
    "plt.xlabel('weekday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FsIxnDzlJkuaoPlcxDT8X4ingHuDwkVQjSZoYfc5B+FwISZqHpnvk6Mem2a+q6uQR1CNJ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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e885c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.workingday, order=[0,1]);\n",
    "plt.xlabel('workingday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+s2ria8CyJDsPVZskacMWep7huVV1D0B7fk7r3wW4a9a4Na1PkjSSaZmITkdf54qxSY5L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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e913320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.weathersit, order=[1,2,3,4]);\n",
    "plt.xlabel('weathersit');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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i1kumkpYUz09fP+J1KVFNTb8Y8tjmSvadaOO+Oxbw282VXpcj4oms1EQ+vLCY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\nopvRwngoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1eef1588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.temp.values, bins=30, kde=True)\n",
    "plt.xlabel('temp', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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48cYjXpfiGwr3BPDwhiMcaOrhy7fMIzWgL5n4z8TCLK6bO57HNh/lZP+g1+X4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fdd8860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.atemp.values, bins=30, kde=True)\n",
    "plt.xlabel('atemp', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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APLmrxeMkcqZ4vMq3ALOdc5cB9wI/P9eGzrn7nXO1zrna0tLSOHxrkdgMDI+w/fAJrqwp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\nu4iID6ncRUR8SOUuIuJDKncRER/6/8D4V8oDS/5sAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e98ea90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.hum.values, bins=30, kde=True)\n",
    "plt.xlabel('hum', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jiLzJ8qnF9PQHeWbXSbIz/Ny+vFqNjRSjFnkU1h5oYfvxDq6qKcWnXxCJQ9fM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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e427860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.windspeed.values, bins=30, kde=True)\n",
    "plt.xlabel('windspeed', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 两两特征之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#get the names of all the columns\n",
    "cols=data.columns \n",
    "\n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "data_corr = data.corr().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12, 12)"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5cyETJ3wJwIMHDxk95lu+GDou3X6nTZtP1WoN8KjZnNq13WnWrGGO1AedDvsv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XgQ6SxgPNgHPDRnLOp7W43ZSkWcCNwAxKljBLzC3xuBRej/jwfTNbFjJPRSU9f9JJ+pioUzg6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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1eb1d0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "plt.savefig('bike_share.png' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "weathersit and temp = 0.99\n",
      "dteday and yr = 0.83\n",
      "temp and windspeed = 0.63\n",
      "weathersit and windspeed = 0.63\n",
      "workingday and atemp = 0.59\n",
      "season and windspeed = 0.57\n"
     ]
    }
   ],
   "source": [
    "#Set the threshold to select only highly correlated attributes\n",
    "threshold = 0.5\n",
    "# List of pairs along with correlation above threshold\n",
    "corr_list = []\n",
    "#size = data.shape[1]\n",
    "size = data_corr.shape[0]\n",
    "\n",
    "#Search for the highly correlated pairs\n",
    "for i in range(0, size): #for 'size' features\n",
    "    for j in range(i+1,size): #avoid repetition\n",
    "        if (data_corr.iloc[i,j] >= threshold and data_corr.iloc[i,j] < 1) or (data_corr.iloc[i,j] < 0 and data_corr.iloc[i,j] <= -threshold):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j]) #store correlation and columns index\n",
    "\n",
    "#Sort to show higher ones first            \n",
    "s_corr_list = sorted(corr_list,key=lambda x: -abs(x[0]))\n",
    "\n",
    "#Print correlations and column names\n",
    "for v,i,j in s_corr_list:\n",
    "    print (\"%s and %s = %.2f\" % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VhltlesTl9AhpMhiEVV78XEMiPXRWahhPQLoQwDcAbEJhHenzACbXslG1MrwD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\nxiML4++TjyycWZcRklFzVY5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Tke0islNENhbrmEFEPi8iLxbPvHlSCv4IQCeAfyieedNQ\n/DN/Xvz5vSLy68Wfb5TCeU8vikifiHyieP2Pi3/nf6NQiPMSEXlWyufrfKj4uOGR138D8L7i91fX\n87kjeicYkIjO7FkAHyp+3gmgqVivbB6AvQAeBPA7SqnrAfQC+Gzxsf9dKXWDUupaFEq0/L5S6hvF\nx/w7pVS7Umqw+NhjxZ9/AsD9xWsrUTgr5wYAvw1gtYg0Fr83F8CdSqmPAvgkgG1KqXYAswAMVwgY\n9jkAB4t/b/mEPCNENXDelQ4iqoEdAGaLSDOAHAoVpTtRCFJbUDi07EfFki8OgO3Fn/ttEfkLAC4K\nNen2AfjfVf7GcBHOHQBuKX7+ewAWiMhwgMqiWIIGxTOSip+/CODvikFys1JqdEAiOicwIBGdgVIq\nLyKvoVBf7jkAe1AYsbwPhWKn31NKdY38GRHJAvgfADqVUodFZBUKAaWaXPFjiPLrUgAsVErtH/W7\nPwCgVANNKfWsiHwYhQKtXxOR1UqpdWfz30qkE6fsiMbnWRSm0p5FoTryf0BhauzHAD4oIlcBhUPX\nRGQ6ysHnWHFN6Y9G/K7TKBxvfSbbUFhbkuLv7qj0IBG5AsAbSqmnUCiKef2oh4z37xFpxYBEND4/\nRKFK8nal1FEAQwB+qJR6E4WsuW4R2YNCgPr1YnbbUyisMW1GuVo3APw9gL8eldRQyX9BoXL5HhF5\nqfh1JR8BsEtE+gAsBPD4yG+qwrlFPyomPDCpgRKL1b6JiCgROEIiIqJEYEAiIqJEYEAiIqJEYEAi\nIqJEYEAiIqJEYEAiIqJEYEAiIqJEYEAiIqJE+P8H9zefhWh1cwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e807fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1ea0b518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Ys2AaHr1xrqxlAUBzLIzvXXWJ7G+QjhuLBH1v8vGqo6+tBoOKwIjuA6ex8MFf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\nJBLQIBFCCIkENEiEEEIiAQ0SIYSQSPD/MusVkq2mIH4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f5f3780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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z0V0sZzVk+E0SAxKZwWrfDcDeMxQ1TGogGmbVrE/X6D2Tznpo5ZYd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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1e7aa668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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SJ50a99xlTJv0iXsCB+589Qf7OO/dbwMaJYM2/uAFLj/7tA6PTESkc8rVgEIu3XIw1qz5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\nBSQREYkFBSQREYmF/x9wrCuBiiFOZwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f2d56a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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kWoTGeNyCKZ2x8WmVLLsj4hZiTCLSVjJtI+u6UArF800EiBjGaLJax7T9xIJG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\nfwAb1TCbNqG/VAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1ecca860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of only the highly correlated pairs\n",
    "for v,i,j in s_corr_list:\n",
    "    sns.pairplot(data, size=6, x_vars=cols[i],y_vars=cols[j] )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
